Encapsulated State better and added a preprocessing function
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parent
147d682c1c
commit
18ad080026
2 changed files with 81 additions and 58 deletions
15
gymclient.py
15
gymclient.py
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@ -18,8 +18,9 @@ class Environment:
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def get_environment_name(self):
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r = requests.get(self.server + "/environment")
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return r.text
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def get_state(self):
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r = requests.get(self.server + "/state")
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def get_state(self, preprocess = False):
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parameter = "?preprocess" if preprocess else ""
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r = requests.get(self.server + "/state" + parameter)
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return pickle.loads(r.content)
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def get_reward(self):
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r = requests.get(self.server + "/reward")
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@ -56,11 +57,13 @@ class Environment:
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##
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# Common API
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##
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def reset(self):
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r = requests.get(self.server + "/reset")
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def reset(self, preprocess = False):
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parameter = "?preprocess" if preprocess else ""
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r = requests.get(self.server + "/reset" + parameter)
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return pickle.loads(r.content)
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def step(self, action):
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r = requests.post(self.server + "/action", data={'id': action})
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def step(self, action, preprocess = False):
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parameter = "?preprocess" if preprocess else ""
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r = requests.post(self.server + "/action" + parameter, data={'id': action})
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content = pickle.loads(r.content)
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return content['state'], content['reward'], content['done'], content['info']
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124
gymserver.py
124
gymserver.py
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@ -13,27 +13,54 @@ log.setLevel(logging.ERROR)
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##
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# OpenAI Gym State
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##
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# environment_name = "Acrobot-v1"
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environment_name = "Pong-v0"
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env = gym.make(environment_name)
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class Environment:
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def __init__(self, environment_name):
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self.sim = gym.make(environment_name)
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self.environment_name = environment_name
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self.reset()
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def step(self, action):
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# [TODO] Check to see if 'action' is valid
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self.state, self.reward, self.done, self.info = self.sim.step(action)
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self.score += self.reward
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def reset(self):
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self.state = self.sim.reset()
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self.reward = 0
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self.score = 0
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self.done = False
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self.info = {}
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def preprocess(self, state):
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raise NotImplementedError
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def get_state(self, preprocess = False, pickleobj = False):
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state = self.state
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if preprocess:
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state = self.preprocess(state)
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if pickleobj:
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state = pickle.dumps(state)
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return state
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# Observations to release to agent
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state = env.reset()
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reward = 0
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score = 0
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done = False
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info = {}
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##
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# Helper Functions
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# Pong Specific Environment Information
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##
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# [TODO] Evaluate whether pickling is the right option here
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def pickle_state():
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global state
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return pickle.dumps(state)
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import cv2
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class PongEnv(Environment):
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def __init__(self):
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super(PongEnv, self).__init__("PongNoFrameskip-v4")
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def preprocess(self, state):
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# Grayscale
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frame = cv2.cvtColor(state, cv2.COLOR_RGB2GRAY)
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# Crop irrelevant parts
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frame = frame[34:194, 15:145] # Crops to shape (160, 130)
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# Downsample
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frame = cv2.resize(frame, (80, 80), interpolation=cv2.INTER_AREA)
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# Normalize
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frame = frame / 255
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return frame
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env = PongEnv()
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##
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# Flask Environment
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##
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@ -41,100 +68,93 @@ app = Flask(__name__)
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@app.route('/environment', methods=['GET'])
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def get_env():
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global env, environment_name
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global env
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if request.args.get('shape') is not None:
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shape = {}
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shape['observation'] = env.observation_space.shape
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shape['action'] = env.action_space.n
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shape['observation'] = env.sim.observation_space.shape
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shape['action'] = env.sim.action_space.n
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return json.dumps(shape)
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return environment_name
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return env.environment_name
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@app.route('/gym', methods=['GET'])
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def get_extra_data():
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global env
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data = {}
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if request.args.get('action_space') is not None:
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data['action_space'] = env.action_space
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data['action_space'] = env.sim.action_space
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if request.args.get('observation_space') is not None:
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data['observation_space'] = env.observation_space
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data['observation_space'] = env.sim.observation_space
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if request.args.get('reward_range') is not None:
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data['reward_range'] = env.reward_range
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data['reward_range'] = env.sim.reward_range
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if request.args.get('metadata') is not None:
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data['metadata'] = env.metadata
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data['metadata'] = env.sim.metadata
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if request.args.get('action_meanings') is not None:
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data['action_meanings'] = env.unwrapped.get_action_meanings()
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data['action_meanings'] = env.sim.unwrapped.get_action_meanings()
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return pickle.dumps(data)
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@app.route('/action_space', methods=['GET'])
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def get_action_space():
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global env
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return pickle.dumps(env.action_space)
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return pickle.dumps(env.sim.action_space)
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@app.route('/observation_space', methods=['GET'])
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def get_observation_space():
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global env
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return pickle.dumps(env.observation_space)
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return pickle.dumps(env.sim.observation_space)
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@app.route('/reward_range', methods=['GET'])
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def get_reward_range():
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global env
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return pickle.dumps(env.reward_range)
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return pickle.dumps(env.sim.reward_range)
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@app.route('/metadata', methods=['GET'])
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def get_metadata():
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global env
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return pickle.dumps(env.metadata)
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return pickle.dumps(env.sim.metadata)
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@app.route('/action_meanings', methods=['GET'])
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def get_action_meanings():
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global env
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return pickle.dumps(env.unwrapped.get_action_meanings())
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return pickle.dumps(env.sim.unwrapped.get_action_meanings())
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@app.route('/state', methods=['GET'])
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def get_state():
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return pickle_state()
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return env.get_state(pickleobj = True, preprocess = request.args.get('preprocess') is not None)
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@app.route('/reward', methods=['GET'])
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def get_reward():
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global score, reward
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global env
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if request.args.get('all') is not None:
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return str(score)
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return str(env.score)
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else:
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return str(reward)
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return str(env.reward)
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@app.route('/done', methods=['GET'])
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def is_done():
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global done
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return str(done)
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global env
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return str(env.done)
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@app.route('/info', methods=['GET'])
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def get_info():
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global info
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return json.dumps(info)
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global env
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return json.dumps(env.info)
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@app.route('/action', methods=['POST'])
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def perform_action():
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global state, reward, done, info, score
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global env
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action = int(request.form['id'])
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# [TODO] Check to see if 'action' is valid
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state, reward, done, info = env.step(action)
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score += reward
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env.step(action)
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content = {}
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content['state'] = state
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content['reward'] = reward
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content['done'] = done
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content['info'] = info
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content['state'] = env.get_state(preprocess = request.args.get('preprocess') is not None)
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content['reward'] = env.reward
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content['done'] = env.done
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content['info'] = env.info
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return pickle.dumps(content)
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@app.route('/reset')
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def reset_env():
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global env, state, reward, done, info, score
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state = env.reset()
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reward = 0
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done = False
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info = {}
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score = 0
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return pickle_state()
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global env
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env.reset()
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return env.get_state(pickleobj = True, preprocess = request.args.get('preprocess') is not None)
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